NAME : Rainer Frotscher COUNTRY : Germany REGISTRATION NUMBER : 10063

GROUP REF. : A2 PREF. SUBJECT : 1 QUESTION N° : 1

Regulated power transformers with elevated importance for network stability are often equipped with an online-monitoring system for the integrated on-load tap-changer (OLTC). Common functions are the monitoring of the drive torque, the oil temperature inside the OLTC oil compartment and the contact wear of the arc-switching contacts. By comparing the live data with type-specific pre-failure- or alarm values, warning messages can be displayed or the tap-changer can be blocked for further operation to avoid major damage. In these issues, the comparison with fixed limits allows a reliable condition-based diagnosis. In other issues, fixed limits may not help, due to the high variance of possible states. What is normal for one individual, may be a fault for another. A typical example is Dissolved Gas Analysis (DGA). Originally designed for transformer oil diagnosis, DGA has also been applied to tap-changers of all kinds, up to now only with moderate success. The main hindrance is the severe deterioration of the OLTC oil by the switching arcs, which cause high amounts of gases and soot. Depending on the OLTC type and the operational data of the application, the absolute gas amounts and gas compositions may vary extremely. With this, the evaluation of the detected gas patterns is a real challenge which has only been partially won. Proven interpretation rules for transformer DGA are only partially applicable to tap-changers. Empirical approaches done by Doble, Duval, IEEE and others are only valid for the tap-changer types which were included in the surveys (mainly reactive, oil-switching compartment types) and so are not applicable to different OLTC architectures. With the introduction of vacuum switching technology, tap-changer DGA gets a new face. By encapsulating the switching arcs inside hermetically sealed vacuum cells, the ppm amounts of combustible gases in the tap-changer oil decrease by the factor of 10²-10³, when compared to the conventional arc-switching-in-oil technique. For these vacuum-switching type OLTCs, the total amounts of gases generated are in the same range as the gases in transformers and can be analysed in the same way. Furthermore, vacuum switching technology offers new chances for device monitoring and diagnosis during service: for the first time, oncoming failures of mechanical, electrical or thermal origin can be detected, due to the low gas levels. For applying DGA on the whole diversity of different OLTC types which can be found worldwide, a closer look on the gas sources itself (see Fig. 1) and their location (OLTC oil compartment, tap selector) is necessary. Because the gas patterns superimpose, each tap-changer model has its specific gassing characteristic. Respecting this, a classification can be set up which helps to categorize different tap-changer models by means of their typical gas patterns. This classification has been published in CIGRE Technical Brochure 443 [1]. DGA data of tap-changers of the same class can be collected in a data base and are principally comparable. If the data base contains 50 data sets at least, statistical methods (as described in IEEE PC57.139) [2] can be applied to generate pre-failure- and alarm values for one OLTC class. These limit values represent a first guess, as the individual DGA fingerprints also depend from dynamic operational parameters, which are not considered in this approach, such as actual load, switching frequency and oil temperature. So, even within one class there may be great variance. To overcome this obstacle, online-monitoring systems for two or three gases are advantageous to observe trends (Fig. 2). Trend analysis allows to track the chronological gassing behaviour and gives individual pre-failure- and alarm values, using the same statistical methods as mentioned above. These limit values can be adapted dynamically,

depending on the actual operating conditions. High gradients without changes of the operating condition most likely represent an upcoming failure. Possible malfunction is represented by electrical or thermal irregularities (the latter ascribed to mechanical misbehavior) and can be detected by an appropriate selection of gases. The Duval triangle for OLTCs [3] represents relations of key gases and so works without fixed limit values. It has been designed for arc-breaking-in-oil tap-changers with high acetylene values during normal service, but astonishingly in many cases it is also applicable to OLTCs with vacuum switching technology. Ongoing work tries to improve the applicability of this triangle by defining variable fault zones which are based on a statistical analysis of online data [4].

Fig. 1: Gas Sources in Tap-Changers

Symbol GassingSource GasPattern DeterminingParameters

arc-switching contacts arcingtransformer load (Iu), step voltage (Ui), transition impedance

vacuum interrupter none sealed system

change-over selector(reversing switch,coarse tap selector)

sparking / arcing

winding capacities (transf. design), recovery voltage,design of change-over selector

main contacts, sliding selector contacts, by-pass contacts

sparkinginductance / resistance ofinternal wiring, contact bouncing

transition resistors heating< 300°C

design value, according to Ui, Iu and R

transition reactance(inside transformer tank)

none no losses

contact heating (coking)of continuously currentcarrying contacts/parts

heating300..1000°C

contact material / platingcontact pressure, joints, ...contact design (cooling conditions)

X

R

Failure !

Warning

Attention

b

[1] CIGRE Working Group D1.32: “DGA in Non-Mineral Oils and Load Tap Changers and

Improved DGA Diagnosis Criteria”, CIGRE Technical Brochure 443, Dec 2010, page 10ff. [2] IEEE PC57.139: „Guide for Dissolved Gas Analysis in Transformer Load Tap Changers“,

Draft Guide D16, Oct 2010 [3] M. Duval: “The Duval triangle for load tap changers, non mineral oils and low temperature

faults in transformer”, IEEE Elec. Insul. Mag., Vol. 24, n°6, Nov-Dec 2008.

Fig. 2: Trend Analysis for Tap-Changer DGA

time

gas

conc

entra

tion

steady state

Wait until steady state Detect normal bandwidth b Detect and review trend dynamic Correlate trend with actual operating conditions

[4] M.Duval, J. Dukarm: ”Application of Duval Triangle 2 to DGA in LTCs”, IEEE WG C57.139,

Nashville meeting, March 13, 2012